code: def test_AUTO_stopping_metric_with_no_sorting_metric_binary():
      print(
          "Check leaderboard with AUTO stopping metric and no sorting metric for binary"
      )
      ds = import_dataset("binary", split=False)
      exclude_algos = ["DeepLearning", "GLM", "StackedEnsemble"]
      aml = H2OAutoML(
          project_name="py_aml_lb_test_auto_stopping_metric_no_sorting_binary",
          seed=automl_seed,
          max_models=10,
          nfolds=2,
          stopping_rounds=1,
          stopping_tolerance=0.5,
          exclude_algos=exclude_algos,
      )
      aml.train(y=ds.target, training_frame=ds.train)
  
      check_leaderboard(
          aml,
          exclude_algos,
          [
              "auc",
              "logloss",
              "aucpr",
              "mean_per_class_error",
              "rmse",
              "mse",
          ],
          "auc",
          True,
      )
      base = get_partitioned_model_names(aml.leaderboard).base
      first = [m for m in base if "XGBoost_1" in m]
      others = [m for m in base if m not in first]
      check_model_property(
          first, "stopping_metric", True, None
      )  # if stopping_rounds == 0, actual value of stopping_metric is set to None
      check_model_property(others, "stopping_metric", True, "logloss")
  
file_path: h2o-3/h2o-py/tests/testdir_algos/automl/leaderboard/pyunit_automl_leaderboard_binary.py
imports: import os
  import sys
  from h2o.automl import H2OAutoML
  from tests import pyunit_utils
  from _leaderboard_utils import check_leaderboard, check_model_property
  from _automl_utils import import_dataset, get_partitioned_model_names
label_desc: Use image node_id 3 for calling a global function with example usage: test_AUTO_stopping_metric_with_no_sorting_metric_binary() without return types